Language Profiles

Three compile-target profiles. Same source, three artifacts, one stable spec. Pick the profile by what you're shipping — production ML, governance kernels, or bare-metal embedded — and mindc emits a binary sized and instrumented for that target.

mind build --profile=<default|systems|embedded>

Flag ships in mindc 0.2.6. Cross-profile linker refusal in 0.3.0.

default

1.8–15.5 µs

frontend latency (parse + typecheck + IR)

Full tensor stdlib, Q16.16 throughout, heap allocator on. The production ML profile — drives the commercial GPU / accelerator backends.

  • Full tensor stdlib (math, linalg, autodiff)
  • Q16.16 fixed-point throughout
  • Heap allocator (dynamic shapes)
  • Engages commercial GPU / NPU / TPU backends
Used by: mind-nerve, MindLLM, rfn-mind, mind-mem

systems

0.8–3 µs

frontend latency

Stripped tensor stdlib + Q16.16 + governance primitives + heap. The control-plane and DIFC-governance profile.

  • Stripped tensor stdlib (no autodiff, no linalg)
  • Q16.16 + governance kernel
  • Heap allocator on
  • Invariant system + audit hash primitives
Used by: 512-MIND (DIFC governance), arch-mind, mind-agents

embedded

0.4–1 µs

frontend latency

Stripped tensor stdlib, no heap, Q16.16, governance. Cortex-M / RISC-V / WASM bare-metal — MIND for environments where malloc is not available.

  • Stripped tensor stdlib
  • Q16.16 + governance kernel
  • No heap (all stack / static)
  • Cortex-M / RISC-V / WASM targets
Used by: Picotronix-MIND, future BCI / edge AI inference

At a glance

Capabilitydefaultsystemsembedded
Frontend latency1.8–15.5 µs0.8–3 µs0.4–1 µs
Tensor stdlibFullStrippedStripped
Q16.16 fixed-point
Heap allocator
Governance kernel
Commercial GPU / accelerator backends
Target environmentsServer, GPU, multi-nodeControl plane, governance, agentsCortex-M, RISC-V, WASM

Read the spec

Profile selection is formalised in mind-spec v1.0 Future Extensions § Language Profiles; implementation lands in mindc Phase 10.6.